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Spring 2004 ECE 734 Course Project Tool for the Generation and Optimization of DFGs from standard filter kernals

Spring 2004 ECE 734 Course Project Tool for the Generation and Optimization of DFGs from standard filter kernals. Murugappan Senthilvelan May 4 th 2004. Motivation. Algorithmic level design space exploration is a task often reserved for human experts

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Spring 2004 ECE 734 Course Project Tool for the Generation and Optimization of DFGs from standard filter kernals

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  1. Spring 2004 ECE 734 Course ProjectTool for the Generation and Optimization of DFGs from standard filter kernals Murugappan Senthilvelan May 4th 2004

  2. Motivation • Algorithmic level design space exploration is a task often reserved for human experts • However in Digital filter domain, algorithms that systematically optimize DFGs have been proposed. • Takes the edge weight matrix and node weight matrices as input • These matrices generated manually by the designer • Need for automatic generation of DFGs from High level language code !

  3. Project Overview

  4. Filter Types Supported • Standard FIR Filter structure: • y(n) = a1 * x(n) + a2 * x(n-1) + a3 * x(n-2) • Standard IIR Filter structure: • y(n) = a1 * y(n-1) + b1 * x(n) + b2 * x(n-1) • Cascaded Filter realizations: • u(n) = a1 * x(n) + a2 * x(n-1) + a3 * x(n-2) y(n) = c1 * u(n) – c2 * y(n-1) • Parallel Filter realizations: • u(n) = a1 * x(n) + a2 * x(n-1) + a3 * x(n-2) v(n) = b1 * x(n) + b2 * x(n-1) + b3 * x(n-2) y(n) = u(n) + v(n)

  5. Netlist Representation • Best way of representing graphs Example netlist: 1 Input 0 3 Output 0 2 Add 1 4 Mul 2 1 2 0 2 3 0 3 4 1 4 2 0

  6. Loop Optimizations • Cutset Retiming • Takes edge weight matrix, node weight matrix and the target iteration period as input and outputs the retimed netlist • Unfolding • Takes edge weight matrix and the unfolding factor as input and outputs the unfolded netlist

  7. Thank you.

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